Twitter conversations on sustainable development goals in Brazilian public universities using natural language processing

Abstract

This study aims to provide insight into the behavior of Twitter conversations related to the Sustainable Development Goals (SDGs) by Brazilian public universities (UPBs) using Natural Language Processing (NLP). To achieve this goal, it was decided to develop descriptive research as it explores the characteristics of conversations focused on Twitter, one of the world's most used social media channels. Natural language processing (NLP) techniques based on the R programming language were used to extract and treat conversations held by the UPBs about the SDG objectives on Twitter. The study period is comprised of the creation of the first Twitter account by the universities until the data collection date, that is, between 2008 and 2022, therefore, 15 years of study, during this period, 326,114 tweets were identified. Evidence points to a substantial evolution in tweet publications by universities over the 15 years of studies. Thus, the practically zero publications in 2008 jumped to more than 15 thousand tweets in 2020. These findings show and confirm that universities use this social media to interact with their stakeholders. In addition, the results indicate that the analyzed universities make few publications on their Twitter about SDGs. In fact, of the 46 universities, only 6 tweeted about the subject, representing 13%. During the 15 years of studies, only 31 tweets were made on the subject. We found that the conversations and positions of universities on this subject in their social networks are few, insufficient, timid, and weak. As a second practical implication of this study, universities as centers of research, knowledge construction, and humanistic training urgently need to position themselves more on this subject in their social networks in order to demonstrate the relevance of the subject and inform about their accomplishments, and the need to everyone got involved in the theme.